N-Alkylamines-Based Micelles Aggregation Number Determination by Fluorescence Techniques

Mobile Phase Aging and Its Impact on Electrospray Ionization of Oligonucleotides

The implementation of fluoroalcohol/alkylamine mobile phase systems in oligonucleotide LC-MS provides a good balance between chromatographic separations and MS sensitivity. Since its introduction, several parameters including mobile phase composition, additive concentration, alkylamine hydrophobicity, and different fluoroalcohols have been carefully evaluated and optimized. While our understanding of this mobile phase system has increased over the years, there are challenges that continue to hinder method performance and remain poorly understood. One of these challenges is the constant loss of MS sensitivity over time, commonly termed mobile phase aging. This study investigates two aging mechanisms associated with loss of MS sensitivity: alkylamine oxidation and aggregate formation. The relationship between pH, organic solvent, oxygen, and mobile phase aging is characterized, and mitigation strategies to extend mobile phase lifetime are discussed.

Cyclen lanthanide-based micellar structures for application as luminescent [Eu(iii)] and magnetic [Gd(iii)] resonance imaging (MRI) contrast agents

The synthesis of coordinatively unsaturated tetra-substituted 1,4,7,10-tetraazacyclododecane (cyclen) lanthanide complexes is described; these structures, possessing hydrophobic (C12-alkyl) tails and hydrophilic head groups, self-assemble into supramolecular micellar structures in aqueous solution, and hence can be utilised as novel contrast agents for MRI.

Influence Prediction of Alkylamines Upon Electrical Percolation of AOT-based Microemulsions Using Artificial Neural Networks

Simulations for the electrical percolation of AOT/iC8/H2O w/o microemulsions added with alkylamines have been carried out by means of multilayer perceptron. Five variables have been elected as inputs: amine concentration, molecular weight, log P, hydrocarbon chain length (as number of carbons), and pKa. As a result, a neural model consisting in five input neurons, two middle layers (with fifteen and ten neurons respectively) and one output neuron was chosen because of its better performance, with a RMSE of 0.54 °C for the prediction set, with R2 = 0.9976.